Build Multi-Agent LLM Applications with AutoGen - Online Course

Build Multi-Agent LLM Applications with AutoGen - Online Course

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Learn to Create Generative AI Agents using LLMs with AutoGen

Updated on Sep, 2026

IT and Software , Other IT and Software, Python

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Welcome to the Build Multi-Agent LLM Applications with AutoGen!

Are you excited about exploring the world of Generative AI? In this course, we'll learn how to create conversable and customizable AI agents powered by Large Language Models. This is a hands-on course with exercises in Python. We'll cover how to combine external tools like APIs and web scrapers with agents. We'll cover advanced techniques like Retrieval Augmented Generation, Prompt Engineering (ReAct) and Task Decomposition. We'll also implement different conversational patterns like group chats and nested chats.

This intermediate-level course is designed for data scientists, machine learning engineers and software engineers aiming to expand their skills into the LLM/Generative AI space.

Getting Started with AutoGen (Basic Concepts)

Large Language Model Agents

Agents with Human-in-the-Loop

Agents with Code Execution Capability

Agents with access to external tools like APIs and web scrapers

Agents in different Conversational Patterns (Sequential, Group, Nested Chats)

Agents with GPT-4 Turbto/DALL-E Image Generation Endpoints

Prompt Engineering Techniques (ReAct) with Agents

Retrieval Augmented Generation (RAG) using Chroma DB and LLM Agents

Task Decomposition (Build Automated LLM Agents)

Message Transformations for LLM Agents

Using Non-OpenAI/Open Source Models with LM Studio

Join me on this journey to explore the world of LLM Agents and Generative AI!

Check out the detailed breakdown of what’s inside the course

Shahzeb Naveed is a passionate and dedicated instructor known for making complex topics easy to understand. With a practical, hands-on teaching approach, he focuses on helping learners build real-world skills rather than just theoretical knowledge. His sessions are engaging, clear, and structured in a way that suits both beginners and intermediate learners. Shahzeb believes in simplifying concepts, encouraging curiosity, and guiding students step by step so they can confidently apply what they learn in real-life scenarios.

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